JSON (JavaScript Object Notation) is a popular way for moving data between various systems, including databases. Starting with 5.7 MySQL implemented a native JSON data type and a set of JSON functions that allows you to perform operations on JSON values.

There was an interesting but hard to read post on StackOverflow about how 'insert select delete' data from a MySQL JSON data type column.  The first line of the writer's problem is a little confusing '
In order to record user mac_address and count mac_address to restrict user login's pc or notebook to control user available max for example (it's work)' but the examples reveled more about what was desired. The idea was to track MAC address used by various users and the author of the question was wondering how to up data a JSON Array of values with JSON_INSERT.  INSERT is for inserting and the better choice would be JSON_ARRAY_APPEND or JSON_ARRAY_INSERT.    But what caught my eye was the second question: Select sql command for json column ? could be …

The MySQL Document Store is a NoSQL JSON document store built upon well known MySQL database technology.  PHP runs about eight percent of the Internet.  So putting the two together is a big priority for me. So this blog post is about getting all this together on a Ubuntu 18.04 system.

Note that I will be teaching PHP and the X DevAPI at Oracle Code One and hopefully in some tutorials/workshops this year.  These session will feature the X DevAPI installed on Virtual Box images and I probably will not have time to cover these steps in detail but I will point to this as reference material.


PHP 7.2 PHP's performance has really skyrocketed with the seven series and the newer betas are looking very impressive.  But to use the new X Devapi you will need to get the shared object for it into your PHP server. 

The MySQL X DevAPI PECL Extension
…

As you know, one of the great new feature in MySQL 8.0 is the Document Store. Now with MySQL you can store your JSON documents in collections and manage them using CRUD operations. NoSQL is now part of MySQL ! Instead of a mix of MongoDB and MySQL, now you can eliminate MongoDB and consolidate with MySQL !

This is a historical meeting of NoSQL and SQL in the same database server!

To use MySQL 8.0 as Document Store, you need to have the X plugin installed (by default since 8.0.11). This plugin enables the X DevAPI that offers a modern programming interface. Clients that communicate with a …

This time we will look at the differences in updating records between MongoDB and the MySQL Document Store.  Syntactically they are pretty different.  I am still following the Getting Started With MongoDB article for example queries.

Updating Records
In Mongo we update thusly:
> db.restaurants.update(
... { "name" : "Juni" },
... {
...  $set: { "cuisine" : "American (new)" },
...  $currentDate: { "lastModified" : true }
... }
... )
WriteResult({ "nMatched" : 1, "nUpserted" : 0, "nModified" : 1 })
>

The same update in the MySQL Document Store can be a lot different.  We could update using SQL or NoSQL.  I would like to update the document with the change to the cuisine and …

Both MongoDB and the MySQL Document Store are JSON document stores.  The syntax differences in the two products are very interesting.  This long will be a comparison of how commands differ between these two products and may evolve into a 'cheat sheet' if there is demand.

I found an excellent Mongo tutorial Getting Started With MongoDB that I use as a framework to explore these two JSON document stores.
The DataI am using the primer-dataset.json file that MongoDB has been using for years  in their documentation, classes, and examples. MySQL has created the world_x data set based on the world database used for years in documentation, classes and examples.  The data set is a collection of JSON documents filled with restaurants around Manhattan.
…

Last time we looked at moving a JSON data set from MongoDB to the MySQL Document Store.  Let's move another and then see how to investigate this date.  We will use the primer-dataset.json that contains data on restaurants around New York City.

Loading Data
The loading of the JSON data set was covered last time but here is the gist. The first step is to fire up the MySQL Shell and login to the server.

 We need a new schema for this data and the example shows one created as nyeats.  The within that new schema a collection is created with the name restaurants.


…

Yesterday I was presenting on the MySQL Document Store and was asked if the _id fields created by the server as an InnoDB primary key is a UUID.  I knew that it was not a UUID but I had to hit the documentations (https://dev.mysql.com/doc/x-devapi-userguide/en/understanding-automatic-document-ids.html) to find out what the document ID really is -- a very interesting piece of information.
The Details If you are inserting a document lacking a _id key, the server generates a value. The _id is 32 bits of a unique prefix (4 bytes), a time stamp (8 bytes), and serial number (16 bytes). The prefix is assigned by the InnoDB Cluster to help ensure uniqueness across a cluster. The timestamp is the encoded startup time of the server.  The serial numbers uses the auto increment offset and auto increment increment server variables .  From the manual page:
This document ID format ensures …

Pretend you have a JSON array of data that looks roughly like the following.

mysql> insert into x(y) values('["a","b","c","d"]');
Query OK, 1 row affected (0.10 sec)

You could get all the values from that array using $[*]

mysql> select y->"$[*]" from x;
+----------------------+
| y->"$[*]"            |
+----------------------+
| ["a", "b", "c", "d"] |
+----------------------+
1 row in set (0.00 sec)

Or the individual members of the array with an index that starts with zero.

mysql> select y->"$[0]" from x;
+-----------+
| y->"$[0]" |
+-----------+
| "a"       |
+-----------+
1 row in set (0.00 sec)

But what about the times you want the last item in the array and really do not want to loop through all the items? How about using …

“The single most important lesson I’ve learned is to keep it simple. I find designers sometimes deliver over-complex, generic solutions that could (in theory) do anything, but in reality are remarkably difficult to operate, and often misunderstood.”–John Ryan

I have interviewed John Ryan, Data Warehouse Solution Architect (Director) at UBS.

RVZ

Q1. You are an experienced Data Warehouse architect, designer and developer. What are the main lessons you have learned in your career?

John Ryan: The single most important lesson I’ve learned is to keep it simple. I find designers sometimes deliver over-complex, generic solutions that could (in theory) do anything, but in reality are remarkably difficult to operate, and often misunderstood. I believe this stems from a lack of understanding of the …